Fianacial moduling Essay Example | Topics and Well Written Essays - 3250 words

Fianacial moduling - Essay Example Both the indices generally followed the Other January effect. Introduction New York Stock Exchange (the US Stock) was officiated on March 18, 1817. London stock exchange (the UK Stock) was founded in 1801. The two stocks combined have the highest Market cap (17.0 trillion) and largest volume (3.1 trillion) in the world [1]. Any movement in these markets pushes stock indices all over the world. Drawing parallels from the common and integrated political and economic interests the host countries of these stock indices, it can be hypnotized that these market are correlated. This paper tries to identify, if any, correlation present between the two indices. As mentioned before the NYSE and the LSE sit on huge pile of money and are influential. Hence it is important to figure out their predictability. This paper assesses the predictability of these stock indices. The paper has been segregated into three segments: First section characterizes time series properties of the stocks namely its ra te of return and its volatility. Second section identifies the January effect. Section three provides an estimation of predictability using long-horizon regressions. For the purpose, monthly data of the stock indices starting from January, 1973 till December, 2004 is analyzed. 1. Time Series Analysis The rate of return is defined as the money earned on an investment (in stocks). Volatility is the measure of fluctuation in the asset (stock) prices. Mean and variance of rate of return and volatility is used to characterize a stock [2]. Curve of distribution of data is measured by Skewness and Kurtosis of the graph. A normal distribution curve is bell shaped symmetric around the mean. A positively skewed distribution is skewed to right. Skewness is measured as 3rd movement of mean. A Kurtosis is a measure of flatness of the top of the graph. Larger value of degree of kurtosis would mean sharper peak [11]. The rate of return of the indices was analyzed against time. The volatility of th e market was also measured. The rate of return was measured as the difference of natural log of the monthly index value. Volatility was measured as the standard deviation of rate of return of the market in a year. Each Index was characterized by its mean of rate of return and its variance of rate of return and volatility. [3] Rate of return Volatility Mean (ln values) Variance Skewness Kurtosis Mean (ln values) Variance Skewness Kurtosis UK 0.010753 0.0034 -0.18 7.31 0.053 0.000682 0.94 1.65 US 0.008991 0.0022 -0.95 6.35 0.043 0.000313 0.72 0.90 The result showed that rate of return on was higher in UK index than in US index by around 20%. Also, the UK market was around 23% more volatile than the US market. Variance of rate of return and volatility showed that UK market was more spread than US stocks. High degree of kurtosis for rate of return of the UK and the US stocks suggested sharp peak of the distribution graph. From degree of kurtosis it could be inferred that volatility was not restricted to certain range of stock return values but was spread over a long value range of returns. It is to be noted that in 31 years starting from Jan 1973, US market grew from 98.66 to 3087.82 (31X) in Dec 2004, while the UK markets grew from 319.53 to 19639.99 (61X) in the same period. Distribution of rate of return data was left tailed for both US and UK stocks while distribution of volatility data was right tailed for both the stocks.